code: def test_sub_policy_coalescing_matrix_correctness():
      @augmentation(
          mag_range=(0, 1),
          randomly_negate=True,
      )
      def first(data, op_id_mag_id):
          return op_id_mag_id
  
      @augmentation(
          mag_range=(1, 2),
          randomly_negate=True,
      )
      def second(data, op_id_mag_id):
          return op_id_mag_id
  
      @augmentation(
          mag_range=(2, 3),
      )
      def third(data, op_id_mag_id):
          return op_id_mag_id
  
      def custom_policy():
          return Policy(
              "MyCustomPolicy",
              14,
              [
                  [
                      (third, 0.5, 1),
                      (second, 1.0, 2),
                      (first, 0.2, 3),
                      (second, 0.25, 4),
                  ],
                  [(first, 0.6, 5)],
                  [(second, 0.1, 6), (third, 0.7, 7)],
                  [
                      (second, 0.8, 8),
                      (first, 0.9, 9),
                      (second, 1.0, 10),
                      (third, 0.2, 11),
                      (first, 0.5, 12),
                      (first, 1.0, 13),
                  ],
              ],
          )
  
      predefined_policies = [
          auto_augment.get_image_net_policy,
          auto_augment.get_reduced_image_net_policy,
          auto_augment.get_svhn_policy,
          auto_augment.get_reduced_cifar10_policy,
          custom_policy,
      ]
      for policy_getter in predefined_policies:
          policy = policy_getter()
          (
              matrix,
              augments,
          ) = auto_augment._sub_policy_to_augmentation_matrix_map(
              policy
          )
          max_sub_policy_len = max(
              len(sub_policy) for sub_policy in policy.sub_policies
          )
          expected_shape = (
              len(policy.sub_policies),
              max_sub_policy_len,
          )
          assert (
              matrix.shape == expected_shape
          ), f"{matrix.shape} {expected_shape} {policy}"
          for i, sub_policy in enumerate(policy.sub_policies):
              for stage_idx in range(max_sub_policy_len):
                  mat_aug = augments[stage_idx][matrix[i, stage_idx]]
                  if stage_idx < len(sub_policy):
                      sub_pol_aug, _, _ = sub_policy[stage_idx]
                      assert (
                          mat_aug is sub_pol_aug
                      ), f"{i} {stage_idx} {mat_aug} {sub_pol_aug} {policy}"
                  else:
                      assert (
                          mat_aug is a.identity
                      ), f"{i} {stage_idx} {mat_aug} {policy}"
  
imports: import itertools
  import os
  import unittest
  import random
  import numpy
  from scipy.stats import chisquare
  from nose2.tools import params
  from nvidia.dali import fn, types
  from nvidia.dali import pipeline_def
  from nvidia.dali.auto_aug import auto_augment, augmentations
  from nvidia.dali.auto_aug.core import augmentation, Policy
  from test_utils import get_dali_extra_path, check_batch
  from nose_utils import assert_raises, assert_warns
label_desc: Use image node_id 11 for calling a global function with example usage: test_sub_policy_coalescing_matrix_correctness() and returns: op_id_mag_id, op_id_mag_id, op_id_mag_id, Policy